DISCUSSION
Our overall results demonstrate rapid evolution in three out of ten
traits under in situ climate manipulations in natural plant
communities after merely 10 years, i.e. at most 10 generations of our
annual study species. This is a remarkably short time span, given that
numerous interacting factors may hamper evolution in natural communities
(Hoffmann & Sgró 2011; Shaw & Etterson 2012). The fact that this
evolutionary response was consistent in two independent sites renders
chance effects, e.g. genetic drift, unlikely to cause these results and
underpins that the evolutionary response was directly driven by
manipulated rainfall. Intriguingly, our multiple independent lines of
evidence corroborate that these changes were adaptive.
After 10 years of artificial drought, phenology had evolved both in
chronological (days to flowering) and ontogenetic (leaf number at
flowering) time. Theory suggests accelerated life-cycles as a drought
avoidance strategy that reduces the risk of mortality before
reproduction (Cohen 1976; Kigel et al. 2011), albeit at the cost
of smaller plant size and hence possibly lower competitive ability
(Liancourt & Tielbörger 2009; Kigel et al. 2011). In line with
theory, plants from dry-manipulated plots flowered earlier and with
fewer leaves than plants from control and wet plots. Moreover, this
rapid evolutionary response paralleled the long-term evolutionary
response of B. didyma along the natural rainfall gradient where
plants from more arid sites flowered earlier; a trend found in many
other annuals along natural rainfall gradients (Kigel et al .
2011; Wolfe & Tonsor 2014; Kurze et al . 2017). Interestingly,
the observed 3-4 days acceleration in phenology corresponds to an
ecological distance of c. 100 mm lower rainfall at origin for
annuals along our study gradient (Kigel et al . 2011; Kurzeet al. 2017). Given the magnitude of rainfall reduction in dry
plots (-90 mm in SA, -160 mm in M), this suggests that phenology could
actually track a substantial part of the imposed change in rainfall. The
adaptivity of accelerated phenology under drought was furthermore
corroborated by our selection analyses under controlled, unconfounded
(Mitchell-Olds & Schmitt 2006) watering conditions in the greenhouse.
Here, earlier flowering with fewer leaves was stronger favored under low
than under high water availability. These multiple lines of evidence –
theory, natural rainfall gradient, selection analyses, and consistency
in both sites – provide compelling evidence that the observed rapid
evolution in phenology was adaptive.
Rapid evolution of earlier phenology under drought was previously
reported from a Californian climate manipulation site (Nguyen et
al. 2016) and from resurrection studies (Franks et al. 2007;
Vigouroux et al. 2011; Nevo et al. 2012; Hamann et
al. 2018). If phenology was reported, no evolution occurred merely in
one perennial (Ravenscroft et al. 2014) or under elevated
CO2 (Grossman & Rice 2014). Therefore, phenology
appears a key trait for rapid drought adaptation in annuals, congruent
with similar suggestions by theory and gradient studies (Cohen 1976;
Kigel et al . 2011; Kurze et al. 2017). These findings may
also indicate that phenology evolves easier than other, possibly more
complex traits. However, more multi-trait studies (e.g. Ravenscroftet al. 2014; Nguyen et al. 2016; Hamann et al.2018) assessing comparable trait-sets are required to confirm this idea.
Here, we also observed rapid evolution in reproductive allocation. As
competition is reduced in drier sites along our gradient (Schiffers &
Tielbörger 2006), theory suggests reduced investment in vegetative
tissue for outgrowing neighbors and increased allocation to reproduction
(Aronson et al. 1990; 1993). In line with theory and in both
sites, plants from dry manipulated plots produced 10-15% more seeds per
vegetative biomass than control plants. Although reproductive allocation
was rarely assessed in climate manipulation studies, a similar tendency
was reported for a perennial herb (Ravenscroft et al . 2014). This
evolutionary response was again congruent with our selection analyses in
the greenhouse, and with the clinal trend in reproductive allocation
along our natural rainfall gradient, and parallel clines in other
species (summarized in Kurze et al. 2017). Thus, in all traits
showing rapid evolution in the field, our independent lines of evidence
demonstrate that these changes were adaptive. Intriguingly, parallel
studies found that many plant community parameters were remarkably
resistant to our climate manipulations (Tielbörger et al . 2014;
Bilton et al . 2016). Though we have studied only a single
species, our current findings suggest that rapid adaptive evolution
possibly contributed to increasing population-level and community-level
resistance to climate change.
Interestingly, evolutionary changes occurred solely in the dry
manipulated plots, i.e. the treatment which increased, rather than
decreased stress for resident plants. Drought likely lead to direct,
rapid exclusion of drought-sensitive and late-flowering genotypes,
especially in dry years. In wet plots, evolution may be slower because
selection was likely driven by competition for additional resources
(Schiffers & Tielbörger 2006) which causes smaller fitness differences,
as was shown by cross-transplants with B. didyma (Ariza &
Tielbörger 2011).
Despite the evidence for rapid adaptive evolution, seven further traits
did not evolve. This was surprising because five of them exhibited
clinal shifts along the rainfall gradient, suggesting that they
contribute to B. didyma’ s long-term evolutionary response to
drier climates: germination fraction, stomata density, height,
vegetative biomass and seed number. In conjunction with existing theory
we had expected corresponding evolution of these traits under climate
manipulations (Westoby 1998; Liu et al. 2012; Tielbörger et
al. 2012; ten Brink et al. 2020). Selection analyses supported
this expectation for vegetative biomass, although not for stomata
density and height; no tests were possible for germination fraction (no
differential watering) and seed number (response variable in selection
analyses). While empirical studies usually focused on (few) traits
exhibiting rapid evolution, non-evolving traits have been reported
before (e.g. Franks 2011; Ravenscroft et al. 2014; Nguyenet al. 2016). One possible explanation for the lack of evolution
in some candidate traits is that selection on them was weakened by
adaptation of the fast-evolving traits, i.e. evolution of further traits
was unnecessary. Alternatively,
the multiple potential constraints
for evolution under natural conditions hindered adaptation in other
traits, e.g. low genetic variation, genetic covariance and trade-offs
among traits (Hoffmann & Sgró 2011; Shaw & Etterson 2012). In our
case, negative genetic covariance potentially hindered evolution in
vegetative biomass (Appendix Fig. S3). The observed rapid evolution in
only a subset of traits may therefore indicate incomplete adaptation to
new conditions, cautioning that climate change may imperil species
despite rapid evolution.
Importantly, most evidence for
rapid adaptive evolution under natural conditions reported rather few
evolving traits (e.g. Franks 2011; Nevo et al. 2012; Ravenscroftet al. 2015; Nguyen et al . 2016). Our findings caution
that focusing on few evolving traits may overestimate the potential of
rapid evolution for climate change adaptation.
High trait plasticity may further retard adaptive evolution (Shaw &
Etterson 2012; Merilä & Hendry 2014; Kelly 2019), but this idea has
rarely been tested in natural populations (Arnold et al. 2019).
Our study, where the three rapidly evolving traits showed three
contrasting magnitudes of plasticity (CV) indicates that plasticity and
evolutionary potential are not necessarily related. However, this
conclusion should be taken with caution because it is based on three
partially correlated traits (Appendix, Fig. S3) which may have evolved
in concert.
Our findings also provide little support for the idea that climate
change leads to increased plasticity as a means to rapidly adjust the
phenotype to novel conditions (Lande 2009; Arnold et al . 2019;
Kelly 2019; Scheiner et al . 2020). Only a single trait, diaspore
weight, had significantly increased plasticity under drought, and days
to flowering showed a similar, non-significant tendency. Both responses,
however, were opposite to the expected adaptive direction (e.g. later,
not earlier flowering under drought; Appendix, Fig. S1), indicating
non-adaptive plasticity (Acasuso-Rivero et al. 2019). Similarly,
no clearly increased plasticity after drought was found by resurrection
studies (Franks 2011; Hamann et al. 2018) and lower plasticity after
CO2 elevation (Grossman & Rice 2014; but see Sultanet al. 2013 for increased plasticity during plant invasion).
Thus, our study joins an –albeit small- body of equivocal evidence
indicating that evolution of increased plasticity is no major pathway
for climate change adaptation.
Overall, our study demonstrates
that rapid evolution may play an important role for climate change
adaptation in natural annual plant populations. The novel setup of our
study – combining in situ climate manipulations with a natural
climatic gradient and selection analyses under controlled conditions –
provided independent, compelling lines of evidence that observed
evolutionary shifts were adaptive. However, with rapid evolution in
merely a subset of well-justified candidate traits, our study emphasizes
the importance of multi-trait studies for assessing whether rapidin situ evolution may safeguard species under climate change.